Get started

This 5-minute tutorial will show you how to run your first jobs with MRQ.

Installation

  • Make sure you have installed the dependencies : Redis and MongoDB
  • Install MRQ with pip install mrq
  • Start a mongo server with mongod &
  • Start a redis server with redis-server &

Write your first task

Create a new directory and write a simple task in a file called tasks.py :

$ mkdir test-mrq && cd test-mrq
$ touch __init__.py
$ vim tasks.py

from mrq.task import Task
import urllib2


class Fetch(Task):

    def run(self, params):

        with urllib2.urlopen(params["url"]) as f:
          t = f.read()
          return len(t)

Run it synchronously

You can now run it from the command line using mrq-run:

$ mrq-run tasks.Fetch url http://www.google.com

2014-12-18 15:44:37.869029 [DEBUG] mongodb_jobs: Connecting to MongoDB at 127.0.0.1:27017/mrq...
2014-12-18 15:44:37.880115 [DEBUG] mongodb_jobs: ... connected.
2014-12-18 15:44:37.880305 [DEBUG] Starting tasks.Fetch({'url': 'http://www.google.com'})
2014-12-18 15:44:38.158572 [DEBUG] Job None success: 0.278229s total
17655

Run it asynchronously

Let's schedule the same task 3 times with different parameters:

$ mrq-run --queue fetches tasks.Fetch url http://www.google.com &&
  mrq-run --queue fetches tasks.Fetch url http://www.yahoo.com &&
  mrq-run --queue fetches tasks.Fetch url http://www.wordpress.com

2014-12-18 15:49:05.688627 [DEBUG] mongodb_jobs: Connecting to MongoDB at 127.0.0.1:27017/mrq...
2014-12-18 15:49:05.705400 [DEBUG] mongodb_jobs: ... connected.
2014-12-18 15:49:05.729364 [INFO] redis: Connecting to Redis at 127.0.0.1...
5492f771520d1887bfdf4b0f
2014-12-18 15:49:05.957912 [DEBUG] mongodb_jobs: Connecting to MongoDB at 127.0.0.1:27017/mrq...
2014-12-18 15:49:05.967419 [DEBUG] mongodb_jobs: ... connected.
2014-12-18 15:49:05.983925 [INFO] redis: Connecting to Redis at 127.0.0.1...
5492f771520d1887c2d7d2db
2014-12-18 15:49:06.182351 [DEBUG] mongodb_jobs: Connecting to MongoDB at 127.0.0.1:27017/mrq...
2014-12-18 15:49:06.193314 [DEBUG] mongodb_jobs: ... connected.
2014-12-18 15:49:06.209336 [INFO] redis: Connecting to Redis at 127.0.0.1...
5492f772520d1887c5b32881

You can see that instead of executing the tasks and returning their results right away, mrq-run has added them to the queue named fetches and printed their IDs.

Now start MRQ's dasbhoard with mrq-dashboard & and go check your newly created queue and jobs on localhost:5555

They are ready to be dequeued by a worker. Start one with mrq-worker and follow it on the dashboard as it executes the queued jobs in parallel.

$ mrq-worker fetches

2014-12-18 15:52:57.362209 [INFO] Starting Gevent pool with 10 worker greenlets (+ report, logs, adminhttp)
2014-12-18 15:52:57.388033 [INFO] redis: Connecting to Redis at 127.0.0.1...
2014-12-18 15:52:57.389488 [DEBUG] mongodb_jobs: Connecting to MongoDB at 127.0.0.1:27017/mrq...
2014-12-18 15:52:57.390996 [DEBUG] mongodb_jobs: ... connected.
2014-12-18 15:52:57.391336 [DEBUG] mongodb_logs: Connecting to MongoDB at 127.0.0.1:27017/mrq...
2014-12-18 15:52:57.392430 [DEBUG] mongodb_logs: ... connected.
2014-12-18 15:52:57.523329 [INFO] Fetching 1 jobs from ['fetches']
2014-12-18 15:52:57.567311 [DEBUG] Starting tasks.Fetch({u'url': u'http://www.google.com'})
2014-12-18 15:52:58.670492 [DEBUG] Job 5492f771520d1887bfdf4b0f success: 1.135268s total
2014-12-18 15:52:57.523329 [INFO] Fetching 1 jobs from ['fetches']
2014-12-18 15:52:57.567747 [DEBUG] Starting tasks.Fetch({u'url': u'http://www.yahoo.com'})
2014-12-18 15:53:01.897873 [DEBUG] Job 5492f771520d1887c2d7d2db success: 4.361895s total
2014-12-18 15:52:57.523329 [INFO] Fetching 1 jobs from ['fetches']
2014-12-18 15:52:57.568080 [DEBUG] Starting tasks.Fetch({u'url': u'http://www.wordpress.com'})
2014-12-18 15:53:00.685727 [DEBUG] Job 5492f772520d1887c5b32881 success: 3.149119s total
2014-12-18 15:52:57.523329 [INFO] Fetching 1 jobs from ['fetches']
2014-12-18 15:52:57.523329 [INFO] Fetching 1 jobs from ['fetches']

You can interrupt the worker with Ctrl-C once it is finished.

Going further

This was a preview on the very basic features of MRQ. What makes it actually useful is that:

  • You can run multiple workers in parallel. Each worker can also run multiple greenlets in parallel.
  • Workers can dequeue from multiple queues
  • You can queue jobs from your Python code to avoid using mrq-run from the command-line.

These features will be demonstrated in a future example of a simple web crawler.